After reading the 'Attention is all you need' article, I understand the general architecture of a transformer. However, it is unclear to me how the feed forward neural network learns.
What I learned about neural nets is that they learn based on a target variable, through back propagation according to a particular loss function.
Looking at the architecture of a Transformer, it is unclear to me what the target variables are in these feed forward nets. Can someone explain this to me?